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Journal Article

Citation

Wawrowski, Białas A, Kajzer A, Kozłowski A, Kurianowicz R, Sikora M, Szymańska-Kwiecień A, Uchroński M, Białczak M, Olejnik M, Michalak M. Sensors (Basel) 2023; 23(6).

Copyright

(Copyright © 2023, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/s23062974

PMID

36991685

PMCID

PMC10059045

Abstract

It seems to be a truism to say that we should pay more and more attention to network traffic safety. Such a goal may be achieved with many different approaches. In this paper, we put our attention on the increase in network traffic safety based on the continuous monitoring of network traffic statistics and detecting possible anomalies in the network traffic description. The developed solution, called the anomaly detection module, is mostly dedicated to public institutions as the additional component of the network security services. Despite the use of well-known anomaly detection methods, the novelty of the module is based on providing an exhaustive strategy of selecting the best combination of models as well as tuning the models in a much faster offline mode. It is worth emphasizing that combined models were able to achieve 100% balanced accuracy level of specific attack detection.


Language: en

Keywords

anomaly detection; cybersecurity; network traffic monitoring

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